FEATSELM

Feature selection map

  [W,R] = FEATSELM(A,CRIT,METHOD,K,T,PAR1,...)

Input
A	Training dataset
CRIT	Name of criterion: 'in-in', 'maha-s', 'NN' or others  (see FEATEVAL) or an untrained classifier V (default: 'NN')
METHOD	'forward' : selection by featself (default) -  'float' : selection by featselp -  'backward': selection by featselb -  'b&b' : branch and bound selection by featselo -  'ind' : individual -  'lr' : plus-l-takeaway-r selection by featsellr -  'sparse' : use sparse untrained classifier CRIT
K	Desired number of features (default: K = 0, return optimal set)
T	Tuning set to be used in FEATEVAL (optional)
PAR1,..	Optional parameters: -  L,R : for 'lr' (default: L = 1, R = 0)

Output
W	Feature selection mapping
R	Matrix with step by step results

Description

Computation of a mapping W selecting K features. This routines offers a  central interface to all other feature selection methods. W can be used  for selecting features in a dataset B using B*W.

See also

mappings, datasets, feateval, featselo, featselb, featseli, featselp, featself, featsellr,